标题： KnowRA：基于知识检索增强的文档级关系抽取方法及全面推理能力 显示英文标题

标题： KnowRA: Knowledge Retrieval Augmented Method for Document-level Relation Extraction with Comprehensive Reasoning Abilities

摘要： 文档级关系抽取（Doc-RE）旨在提取跨越多个句子的实体之间的关系。因此，与句子级关系抽取相比，Doc-RE需要更全面的推理能力，涉及实体、上下文和外部常识知识之间的复杂跨句交互。 然而，大多数现有的Doc-RE方法专注于优化单一推理能力，但缺乏利用外部知识对长文档进行全面推理的能力。 为了解决这些问题，提出了一种名为KnowRA的知识检索增强方法，该方法具有全面推理能力，可以自主决定是否接受外部知识以辅助Doc-RE。 首先，我们构建了一个文档图用于语义编码，并集成了共指消解模型以增强共指推理能力。 然后，通过检索常识推理的外部知识库来扩展文档图成为文档知识图，并提出了一种新的知识过滤方法以筛选出无关知识。 最后，我们提出了轴向注意力机制，以建立与中介实体的直接和间接关联，从而实现跨句逻辑推理。 在两个数据集上进行的广泛实验验证了我们方法的有效性，相比最先进的基线方法有所提升。 我们的代码可在https://anonymous.4open.science/r/KnowRA获取。 显示英文摘要

摘要： Document-level relation extraction (Doc-RE) aims to extract relations between entities across multiple sentences. Therefore, Doc-RE requires more comprehensive reasoning abilities like humans, involving complex cross-sentence interactions between entities, contexts, and external general knowledge, compared to the sentence-level RE. However, most existing Doc-RE methods focus on optimizing single reasoning ability, but lack the ability to utilize external knowledge for comprehensive reasoning on long documents. To solve these problems, a knowledge retrieval augmented method, named KnowRA, was proposed with comprehensive reasoning to autonomously determine whether to accept external knowledge to assist DocRE. Firstly, we constructed a document graph for semantic encoding and integrated the co-reference resolution model to augment the co-reference reasoning ability. Then, we expanded the document graph into a document knowledge graph by retrieving the external knowledge base for common-sense reasoning and a novel knowledge filtration method was presented to filter out irrelevant knowledge. Finally, we proposed the axis attention mechanism to build direct and indirect associations with intermediary entities for achieving cross-sentence logical reasoning. Extensive experiments conducted on two datasets verified the effectiveness of our method compared to the state-of-the-art baselines. Our code is available at https://anonymous.4open.science/r/KnowRA.